Performance Comparison of Detection, Recognition and Tracking Rates of the different Algorithms

Abstract

This article discusses the approach of human detection and tracking in a homogeneous domain using surveillance cameras. This is a vast area in which significant research has been taking place from more than a decade and the paper is about detection of a human and its face in a given video and stores Local Binary Pattern Histogram (LBPH) features of the detected faces. Once a human is detected in the video, that person will be given a label and him/her is tracked in different video taken by multiple cameras by the application of machine learning and image processing with the help of OpenCV. Many algorithms were used for detecting, recognizing and tracking till date, thus in this paper, main thing is the comparison of the proposed algorithm with some among the state-of-the-art algorithms. And also shows how the proposed algorithm is better than the other chosen algorithms.

Deep Neural Network Design and Implementation for Predicting Malignancy of Cancer Tumors

“…Breast cancer is the second most common cancer among women in the United States [1] . In the united states in 2019, there will be around 268,600 new cases of breast cancer, and an estimated of 41,760 women will die from breast cancer [1] .…”

“…Breast cancer is the second most common cancer among women in the United States [1] . In the united states in 2019, there will be around 268,600 new cases of breast cancer, and an estimated of 41,760 women will die from breast cancer [1] . In recent years, incidence rates have expanded marginally by 0.3% every year [1] .Death rates from female breast cancer dropped 40% from 1989 to 2016.…”

“…In the united states in 2019, there will be around 268,600 new cases of breast cancer, and an estimated of 41,760 women will die from breast cancer [1] . In recent years, incidence rates have expanded marginally by 0.3% every year [1] .Death rates from female breast cancer dropped 40% from 1989 to 2016. Since 2007 breast cancer death rates have been consistent in women younger than 50, however have kept on decreasing in older women [1] .…”

“…In recent years, incidence rates have expanded marginally by 0.3% every year [1] .Death rates from female breast cancer dropped 40% from 1989 to 2016. Since 2007 breast cancer death rates have been consistent in women younger than 50, however have kept on decreasing in older women [1] . These decreases are believed to be the result of finding breast cancer earlier through screening and increased awareness, as well as better treatments [1] .…”

“…Since 2007 breast cancer death rates have been consistent in women younger than 50, however have kept on decreasing in older women [1] . These decreases are believed to be the result of finding breast cancer earlier through screening and increased awareness, as well as better treatments [1] . Breast cancer cells usually form a tumor that can often be seen on an x-ray or felt as a lump.…”